org.deeplearning4j.nn.conf.layers.misc

Class ElementWiseMultiplicationLayer

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.BaseLayer

org.deeplearning4j.nn.conf.layers.FeedForwardLayer

org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class ElementWiseMultiplicationLayer
extends FeedForwardLayer

Elementwise multiplication layer with weights: implements out = activationFn(input .* w + b) where:
- w is a learnable weight vector of length nOut
- ".*" is element-wise multiplication
- b is a bias vector

Note that the input and output sizes of the element-wise layer are the same for this layer

created by jingshu

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	ElementWiseMultiplicationLayer.Builder

Field Summary

Fields inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

nIn, nOut

Fields inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer

activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iUpdater, regularization, regularizationBias, weightInitFn, weightNoise

Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer

constraints, iDropout, layerName

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	ElementWiseMultiplicationLayer()
protected	ElementWiseMultiplicationLayer(ElementWiseMultiplicationLayer.Builder builder)

Method Summary

Modifier and Type	Method and Description
ElementWiseMultiplicationLayer	clone()
LayerMemoryReport	getMemoryReport(InputType inputType) This is a report of the estimated memory consumption for the given layer
ParamInitializer	initializer()
Layer	instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, org.nd4j.linalg.api.buffer.DataType networkDataType)

Methods inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

getOutputType, getPreProcessorForInputType, isPretrainParam, setNIn

Methods inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer

getGradientNormalization, getRegularizationByParam, getUpdaterByParam, resetLayerDefaultConfig

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer

initializeConstraints, setDataType

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.deeplearning4j.nn.api.TrainingConfig

getGradientNormalizationThreshold, getLayerName

Constructor Detail

ElementWiseMultiplicationLayer

protected ElementWiseMultiplicationLayer()

ElementWiseMultiplicationLayer

protected ElementWiseMultiplicationLayer(ElementWiseMultiplicationLayer.Builder builder)

Method Detail

clone

public ElementWiseMultiplicationLayer clone()

Overrides:

clone in class BaseLayer

instantiate

public Layer instantiate(NeuralNetConfiguration conf,
                         Collection<TrainingListener> trainingListeners,
                         int layerIndex,
                         INDArray layerParamsView,
                         boolean initializeParams,
                         org.nd4j.linalg.api.buffer.DataType networkDataType)

Specified by:

instantiate in class Layer

initializer

public ParamInitializer initializer()

Specified by:

initializer in class Layer

Returns:

The parameter initializer for this model

getMemoryReport

public LayerMemoryReport getMemoryReport(InputType inputType)

This is a report of the estimated memory consumption for the given layer

Specified by:

getMemoryReport in class Layer

Parameters:

inputType - Input type to the layer. Memory consumption is often a function of the input type

Returns:

Memory report for the layer